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Emerging Approaches in Hydrology and Water Resources

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Earth Sciences".

Deadline for manuscript submissions: closed (30 September 2024) | Viewed by 3421

Special Issue Editor


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Guest Editor
Center for Complex Hydrosystems Research, The University of Alabama, Tuscaloosa, AL 35401, USA
Interests: hydrological modeling; machine learning; artificial intelligence; uncertainty analysis; climate change; flood forecasting; drought forecasting; hydrodynamic modeling; extreme hydrological events; water resources management

Special Issue Information

Dear Colleagues,

This Special Issue of Applied Sciences is dedicated to exploring the latest emerging approaches in hydrology and water resources, with a focus on their applications in addressing the challenges of a changing climate. Specifically, we seek contributions that showcase innovative approaches in hydrological modeling, uncertainty analysis, flood and drought forecasting, hydrodynamic modeling, and extreme hydrological events.

We invite papers that highlight novel approaches to hydrological modeling, such as machine learning, deep learning, and other forms of artificial intelligence, and their potential applications in water resources management. We are also interested in papers that examine innovative approaches to uncertainty analysis in hydrology and climate change, as well as those that demonstrate new techniques for flood and drought forecasting.

In addition, we welcome contributions that showcase emerging approaches to hydrodynamic modeling and simulation, and their potential for improving our understanding of complex water systems. Finally, we invite papers that explore new methods for detecting, monitoring, and responding to extreme hydrological events, such as floods, droughts, and landslides.

We encourage original research papers, review articles, and case studies that demonstrate the innovative applications of emerging approaches in hydrology and water resources management. The goal of this Special Issue is to bring together researchers and practitioners from diverse backgrounds to share their insights, experiences, and best practices in using emerging approaches to address the complex challenges of hydrology and water resources management.

We hope that this Special Issue will inspire new research collaborations and advance our understanding of the role of emerging approaches in shaping the future of hydrology and water resources management.

Dr. Majid Mirzaei
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • hydrological modeling
  • machine learning
  • artificial intelligence
  • uncertainty analysis
  • climate change
  • flood forecasting
  • drought forecasting
  • hydrodynamic modeling
  • extreme hydrological events
  • water resources management
  • remote sensing
  • GIS
  • water quality modeling
  • urban hydrology
  • watershed management
  • snow hydrology
  • reservoir management
  • water allocation
  • water policy
  • sustainable water management

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Related Special Issue

Published Papers (2 papers)

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Research

23 pages, 16012 KiB  
Article
Investigation of Flood Hazard Susceptibility Using Various Distance Measures in Technique for Order Preference by Similarity to Ideal Solution
by Hüseyin Akay and Müsteyde Baduna Koçyiğit
Appl. Sci. 2024, 14(16), 7023; https://doi.org/10.3390/app14167023 - 10 Aug 2024
Cited by 1 | Viewed by 1407
Abstract
In the present study, flood hazard susceptibility maps generated using various distance measures in the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) were analyzed. Widely applied distance measures such as Euclidean, Manhattan, Chebyshev, Jaccard, and Soergel were used in [...] Read more.
In the present study, flood hazard susceptibility maps generated using various distance measures in the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) were analyzed. Widely applied distance measures such as Euclidean, Manhattan, Chebyshev, Jaccard, and Soergel were used in TOPSIS to generate flood hazard susceptibility maps of the Gökırmak sub-basin located in the Western Black Sea Region, Türkiye. A frequency ratio (FR) and weight of evidence (WoE) were adapted to hybridize the nine flood conditioning factors considered in this study. The Receiver Operating Characteristic (ROC) analysis and Seed Cell Area Index (SCAI) were used for the validation and testing of the generated flood susceptibility maps by extracting 70% and 30% of the inventory data of the generated flood susceptibility map for validation and testing, respectively. When the Area Under Curve (AUC) and SCAI values were examined, it was found that the Manhattan distance metric hybridized with the FR method gave the best prediction results with AUC values of 0.904 and 0.942 for training and testing, respectively. Furthermore, the natural break method was found to give the best predictions of the flood hazard susceptibility classes. So, the Manhattan distance measure could be preferred to Euclidean for flood susceptibility mapping studies. Full article
(This article belongs to the Special Issue Emerging Approaches in Hydrology and Water Resources)
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25 pages, 4749 KiB  
Article
Impact of Climate Change on the Major Eco-Hydrological Parameters in the Dongting Lake Basin
by Fang Zheng, Yiqun Gan, Liu Yang and Jing Wu
Appl. Sci. 2023, 13(17), 9515; https://doi.org/10.3390/app13179515 - 22 Aug 2023
Cited by 3 | Viewed by 1250
Abstract
Quantifying the impacts of climate change on evapotranspiration (ET) and gross primary production (GPP) in the Dongting Lake Basin is essential for assessing water scarcity and implementing sustainable development strategies. Premised on actual measurements and remote sensing data from 47 stations, the impact [...] Read more.
Quantifying the impacts of climate change on evapotranspiration (ET) and gross primary production (GPP) in the Dongting Lake Basin is essential for assessing water scarcity and implementing sustainable development strategies. Premised on actual measurements and remote sensing data from 47 stations, the impact of climate change on eco-hydrological parameters in the Dongting Lake Basin was analyzed in the present study using the BESS model (The Breathing Earth System Simulator), ridge regression analysis, stepwise regression model and time-lag analysis. The results reveal that: (1) the Dongting Lake Basin has been warm and arid over the last four decades, with the frequent occurrence of extreme climate events. Vegetation carbon sequestration capacity exhibited a slightly upward trend with 0.0081 g C m−2 d−1/year from 2000–2017. ET changed with rates of −3.309 mm/year, with possible risk conflicts between water demand and supply in the future. (2) The increasing temperature was the main driver of ET enhancement in the Dongting Lake Basin. Meanwhile, both temperature and precipitation were found to be the dominant drivers of GPP enhancement. The effect of temperature on GPP was found to be greater in the areas covered by crops and tree vegetation, and natural vegetation was more strongly influenced by precipitation than radiation. (3) Extreme temperature events have had a significant impact on evapotranspiration (ET) and gross primary production (GPP) in the Dongting Lake Basin. Specifically, the cold index in extreme temperature events was found to significantly affect ET, while the heat index in extreme temperature events significantly affected GPP. Additionally, both ET and GPP were found to respond to extreme precipitation events in the region. The results of the study established that vegetation is highly sensitive to temperature, especially temperature extremes, and that precipitation also has a stressful effect. Increasing temperatures and precipitation within a range benefit vegetation productivity. (4) In the Dongting Lake Basin, we found that different climatic factors produced different time lag effects on GPP and ET by time lag analysis. This study highlights the lag effects of climate factors and extreme climate events on eco-hydrological parameters. We suggest incorporating the effects into simulation models of eco-hydrological parameters. This will lead to a better understanding of the variation of eco-hydrological parameters under climate change. Full article
(This article belongs to the Special Issue Emerging Approaches in Hydrology and Water Resources)
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